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# Tensorflow.js tf.range() Function

• Last Updated : 28 Apr, 2021

Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment.

The tf. range() is used to create a new tf.Tensor1D filled with the numbers in the range provided with the help of start, stop, step, and dtype.

Syntax:

`tf.range(start, stop, step, dtype)`

Parameters:

• start: It is an integer start value that denotes the starting number of the range.
• stop: It is an integer stop value that denotes the ending number of the range, and it is not included.
• step: It is an integer increment which is 1 or -1 by default. It is an optional parameter.
• dtype: It is the data type of the output tensor. It defaults to ‘float32’. It is an optional parameter.

Return Value: It returns a new Tensor1D object.

Example 1: In this example, we try to generate a range of numbers from 1 to 9 with default step 1.

## Javascript

 `// Importing the tensorflow.js library ` `import * as tf from ``"@tensorflow/tfjs"` ` `  `// Creating the tensor1D array by tf.range ` `var` `val = tf.range(1,10); ` ` `  `// Printing the tensor ` `val.print() `

Output:

```Tensor
[1, 2, 3, 4, 5, 6, 7, 8, 9]```

Example 2: In this example, we try to generate odd numbers between 1 and 10 using step size 2.

## Javascript

 `// Importing the tensorflow.js library ` `import * as tf from ``"@tensorflow/tfjs"` ` `  `// Creating the tensor1D array by tf.range ` `var` `val = tf.range(1,10,2); ` ` `  `// Printing the tensor ` `val.print() `

Output:

```Tensor
[1, 3, 5, 7, 9]```

Example 3: In this example, we try to generate even numbers between 0 and 10 using step size 2.

## Javascript

 `// Importing the tensorflow.js library ` `import * as tf from ``"@tensorflow/tfjs"` ` `  `// Creating the tensor1D array by tf.range ` `var` `val = tf.range(0,10,2); ` ` `  `// Printing the tensor ` `val.print()`

Output:

```Tensor
[0, 2, 4, 6, 8],```

Example 4: In this example, we will try to use the dtype parameter.

## Javascript

 `// Importing the tensorflow.js library ` `import * as tf from ``"@tensorflow/tfjs"` ` `  `// Creating the tensor1D array by tf.range ` `var` `val = tf.range(-1,1,1,``'bool'``); ` ` `  `// Printing the tensor ` `val.print() `

Output:

```​Tensor
[true, false]```

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